Conference On Machine Processing Remotely Sensed Data
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Conference On Machine Processing Remotely Sensed Data
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Author :
language : en
Publisher:
Release Date : 1973
Conference On Machine Processing Remotely Sensed Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with Remote sensing categories.
Conference On Machine Processing Of Remotely Sensed Data
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Author :
language : en
Publisher:
Release Date : 1973
Conference On Machine Processing Of Remotely Sensed Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with Electronic data processing categories.
Conference On Machine Processing Of Remotely Sensed Data
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Author : Conference on machine processing of remotely sensed data
language : en
Publisher:
Release Date : 1973
Conference On Machine Processing Of Remotely Sensed Data written by Conference on machine processing of remotely sensed data and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with categories.
Big Data Analytics For Satellite Image Processing And Remote Sensing
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Author : Swarnalatha, P.
language : en
Publisher: IGI Global
Release Date : 2018-03-09
Big Data Analytics For Satellite Image Processing And Remote Sensing written by Swarnalatha, P. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-09 with Technology & Engineering categories.
The scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Big Data Analytics for Satellite Image Processing and Remote Sensing is a critical scholarly resource that examines the challenges and difficulties of implementing big data in image processing for remote sensing and related areas. Featuring coverage on a broad range of topics, such as distributed computing, parallel processing, and spatial data, this book is geared towards scientists, professionals, researchers, and academicians seeking current research on the use of big data analytics in satellite image processing and remote sensing.
Machine Processing Of Remotely Sensed Data With Special Emphasis On Range Forest And Wetlands Assessment
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Author : P. G. Burroff
language : en
Publisher:
Release Date : 1981
Machine Processing Of Remotely Sensed Data With Special Emphasis On Range Forest And Wetlands Assessment written by P. G. Burroff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981 with Forests and forestry categories.
Remote Sensing For Environmental Sciences
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Author : E. Schanda
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Remote Sensing For Environmental Sciences written by E. Schanda and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
The public's serious concern about the uncertainties and dangers of the conse quences of human activities on environmental quality demands policies to control the situation and to prevent its deterioration. But far-reaching decisions on the environmental policy are impaired or even made impossible as long as the relevant ecological relations are not sufficiently understood and large-scale quantitative information on the most important parameters is not available in sufficient quality and quantity. The techniques of remote sensing offer new ways of procuring data on natural phenomena with three main advantages - the large distance between sensor and object prevents interference with the environmental conditions to be measured, - the potentiality for large-scale and even global surveys yields a new dimension for the investigations of the environmental parameters, - the extremely wide, spectral range covered by the whole diversity of sensors discloses many properties of the environmental media not detectable within a single wave band (as e.g. the visible). These significant additions to the conventional methods of environmental studies and the particular qualification of several remote sensing methods for quantitative determination of the natural parameters makes this new investigation technique an important tool both to the scientists studying the ecological relationship and the administration in charge of the environmental planning and protection.
Kernel Methods For Remote Sensing Data Analysis
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Author : Gustau Camps-Valls
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-03
Kernel Methods For Remote Sensing Data Analysis written by Gustau Camps-Valls and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-03 with Technology & Engineering categories.
Kernel methods have long been established as effective techniques in the framework of machine learning and pattern recognition, and have now become the standard approach to many remote sensing applications. With algorithms that combine statistics and geometry, kernel methods have proven successful across many different domains related to the analysis of images of the Earth acquired from airborne and satellite sensors, including natural resource control, detection and monitoring of anthropic infrastructures (e.g. urban areas), agriculture inventorying, disaster prevention and damage assessment, and anomaly and target detection. Presenting the theoretical foundations of kernel methods (KMs) relevant to the remote sensing domain, this book serves as a practical guide to the design and implementation of these methods. Five distinct parts present state-of-the-art research related to remote sensing based on the recent advances in kernel methods, analysing the related methodological and practical challenges: Part I introduces the key concepts of machine learning for remote sensing, and the theoretical and practical foundations of kernel methods. Part II explores supervised image classification including Super Vector Machines (SVMs), kernel discriminant analysis, multi-temporal image classification, target detection with kernels, and Support Vector Data Description (SVDD) algorithms for anomaly detection. Part III looks at semi-supervised classification with transductive SVM approaches for hyperspectral image classification and kernel mean data classification. Part IV examines regression and model inversion, including the concept of a kernel unmixing algorithm for hyperspectral imagery, the theory and methods for quantitative remote sensing inverse problems with kernel-based equations, kernel-based BRDF (Bidirectional Reflectance Distribution Function), and temperature retrieval KMs. Part V deals with kernel-based feature extraction and provides a review of the principles of several multivariate analysis methods and their kernel extensions. This book is aimed at engineers, scientists and researchers involved in remote sensing data processing, and also those working within machine learning and pattern recognition.
Earth Resources
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Author :
language : en
Publisher:
Release Date : 1983
Earth Resources written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Astronautics in earth sciences categories.
Remote Sensing Image Processing
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Author : Gustavo Camps-Valls
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2011
Remote Sensing Image Processing written by Gustavo Camps-Valls and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.
Earth observation is the field of science concerned with the problem of monitoring and modeling the processes on the Earth surface and their interaction with the atmosphere. The Earth is continuously monitored with advanced optical and radar sensors. The images are analyzed and processed to deliver useful products to individual users, agencies and public administrations. To deal with these problems, remote sensing image processing is nowadays a mature research area, and the techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, data coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This book covers some of the fields in a comprehensive way. Table of Contents: Remote Sensing from Earth Observation Satellites / The Statistics of Remote Sensing Images / Remote Sensing Feature Selection and Extraction / {Classification / Spectral Mixture Analysis / Estimation of Physical Parameters
Remotely Sensed Data Characterization Classification And Accuracies
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Author : Ph.D., Prasad S. Thenkabail
language : en
Publisher: CRC Press
Release Date : 2015-10-02
Remotely Sensed Data Characterization Classification And Accuracies written by Ph.D., Prasad S. Thenkabail and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-02 with Technology & Engineering categories.
A volume in the Remote Sensing Handbook series, Remotely Sensed Data Characterization, Classification, and Accuracies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Land Resources Monitoring, Modeling, and Mapping with Remote Sensing, and Remote Sensing of Water Resources, Disasters, and Urban Studies. This volume demonstrates the experience, utility, methods, and models used in studying a wide array of remotely sensed data characterization, classification, and accuracies for terrestrial applications. Leading experts on global geographic coverage, study areas, and array of satellite and sensors contribute to this unique handbook. This theoretical as well as highly practical book represents a thorough history of advancement in the field over last 50 years, bringing us to where we are now, and highlighting future possibilities. Highlights include: Fundamental and advanced topics in remote-sensing satellites and sensors Remote sensing data calibration, normalization, harmonization, and synthesis Optical, Radar, LiDAR, thermal, hyperspectral, and other satellite sensors, normalization of remotely sensed data, and data degradations Digital image processing, urban image classification, and image classification methods in land use\land cover, cropland, change detection studies Enhanced vegetation indices and standardization of vegetation indices Object-based image analysis (OBIA) and geospatial data integration LiDAR data processing and applications Geoprocessing, GIS, and GIScience GNSS applications Crowdsourcing and cloud computing Google Earth for Earth Sciences Map accuracies Remote-sensing law or space law, and a host of other topics.